Applied Bayesian Inference in R using MCMCpack

Sampling) project is a long-running project to provide a user-friendly language and environment for Bayesian inference. The first article, by Andrew Thomas and colleagues, describes the BRugs package which provides an R interface to the OpenBUGS engine. The second article by Andrew Thomas describes the BUGS language itself and the design philosophy behind it. Somewhat unusually for an article in R News, this article does not describe any R software, but it is included to highlight some of the differences in the way statistical models are represented in R and OpenBUGS. The issue ends with an article by Jouni Kerman and Andrew Gelman, who give a personal perspective on what the next generation of Bayesian software may look like, and preview some of their own work in this area, notably the rv package for representing simulation-based random variables, and the forthcoming “Universal Markov Chain Sampler” package, Umacs.